Recurrent Implicit Neural Graph for Deformable Tracking in Endoscopic Videos.
Adam SchmidtOmid MohareriSimon P. DiMaioSeptimiu E. SalcudeanPublished in: MICCAI (4) (2022)
Keyphrases
- endoscopic video
- moving camera
- real time
- video surveillance
- video sequences
- video dataset
- network architecture
- kalman filter
- directed graph
- surveillance videos
- video images
- input video
- articulated objects
- visual tracking
- object tracking
- deformable models
- hand detection
- neural network
- video frames
- random walk
- video data
- appearance model
- video stabilization
- particle filter
- weighted graph
- bipartite graph
- human activities
- feed forward
- mean shift
- foreground background segmentation
- video content
- video database
- image sequences
- graph representation
- motion model
- successive frames
- computer vision
- recurrent neural networks
- image segmentation
- traffic scenes
- artificial neural networks
- video scene
- object detection
- moving target
- action recognition
- degrees of freedom
- dynamic scenes
- motion segmentation
- structured data